Spiking activity in the visual thalamus is coupled to pupil dynamics across temporal scales.

The processing of sensory information, even at early stages, is influenced by the internal state of the animal. Internal states, such as arousal, are often characterized by relating neural activity to a single "level" of arousal, defined by a behavioral indicator such as pupil size. In this study, we expand the understanding of arousal-related modulations in sensory systems by uncovering multiple timescales of pupil dynamics and their relationship to neural activity. Specifically, we observed a robust coupling between spiking activity in the mouse dorsolateral geniculate nucleus (dLGN) of the thalamus and pupil dynamics across timescales spanning a few seconds to several minutes. Throughout all these timescales, 2 distinct spiking modes-individual tonic spikes and tightly clustered bursts of spikes-preferred opposite phases of pupil dynamics. This multi-scale coupling reveals modulations distinct from those captured by pupil size per se, locomotion, and eye movements. Furthermore, coupling persisted even during viewing of a naturalistic movie, where it contributed to differences in the encoding of visual information. We conclude that dLGN spiking activity is under the simultaneous influence of multiple arousal-related processes associated with pupil dynamics occurring over a broad range of timescales.

Aperiodic components of local field potentials reflect inherent differences between cortical and subcortical activity.

Information flow in brain networks is reflected in local field potentials that have both periodic and aperiodic components. The 1/fχ aperiodic component of the power spectra tracks arousal and correlates with other physiological and pathophysiological states. Here we explored the aperiodic activity in the human thalamus and basal ganglia in relation to simultaneously recorded cortical activity. We elaborated on the parameterization of the aperiodic component implemented by specparam (formerly known as FOOOF) to avoid parameter unidentifiability and to obtain independent and more easily interpretable parameters. This allowed us to seamlessly fit spectra with and without an aperiodic knee, a parameter that captures a change in the slope of the aperiodic component. We found that the cortical aperiodic exponent χ, which reflects the decay of the aperiodic component with frequency, is correlated with Parkinson's disease symptom severity. Interestingly, no aperiodic knee was detected from the thalamus, the pallidum, or the subthalamic nucleus, which exhibited an aperiodic exponent significantly lower than in cortex. These differences were replicated in epilepsy patients undergoing intracranial monitoring that included thalamic recordings. The consistently lower aperiodic exponent and lack of an aperiodic knee from all subcortical recordings may reflect cytoarchitectonic and/or functional differences. SIGNIFICANCE STATEMENT: The aperiodic component of local field potentials can be modeled to produce useful and reproducible indices of neural activity. Here we refined a widely used phenomenological model for extracting aperiodic parameters (namely the exponent, offset and knee), with which we fit cortical, basal ganglia, and thalamic intracranial local field potentials, recorded from unique cohorts of movement disorders and epilepsy patients. We found that the aperiodic exponent in motor cortex is higher in Parkinson's disease patients with more severe motor symptoms, suggesting that aperiodic features may have potential as electrophysiological biomarkers for movement disorders symptoms. Remarkably, we found conspicuous differences in the aperiodic parameters of basal ganglia and thalamic signals compared to those from neocortex.

Multi-timescale neuromodulation strategy for closed-loop deep brain stimulation in Parkinson's disease.

Objective.Beta triggered closed-loop deep brain stimulation (DBS) shows great potential for improving the efficacy while reducing side effect for Parkinson's disease. However, there remain great challenges due to the dynamics and stochasticity of neural activities. In this study, we aimed to tune the amplitude of beta oscillations with different time scales taking into account influence of inherent variations in the basal ganglia-thalamus-cortical circuit.Approach. A dynamic basal ganglia-thalamus-cortical mean-field model was established to emulate the medication rhythm. Then, a dynamic target model was designed to embody the multi-timescale dynamic of beta power with milliseconds, seconds and minutes. Moreover, we proposed a closed-loop DBS strategy based on a proportional-integral-differential (PID) controller with the dynamic control target. In addition, the bounds of stimulation amplitude increments and different parameters of the dynamic target were considered to meet the clinical constraints. The performance of the proposed closed-loop strategy, including beta power modulation accuracy, mean stimulation amplitude, and stimulation variation were calculated to determine the PID parameters and evaluate neuromodulation performance in the computational dynamic mean-field model.Main results. The Results show that the dynamic basal ganglia-thalamus-cortical mean-field model simulated the medication rhythm with the fasted and the slowest rate. The dynamic control target reflected the temporal variation in beta power from milliseconds to minutes. With the proposed closed-loop strategy, the beta power tracked the dynamic target with a smoother stimulation sequence compared with closed-loop DBS with the constant target. Furthermore, the beta power could be modulated to track the control target under different long-term targets, modulation strengths, and bounds of the stimulation increment.Significance. This work provides a new method of closed-loop DBS for multi-timescale beta power modulation with clinical constraints.

Specific connectivity optimizes learning in thalamocortical loops.

Thalamocortical loops have a central role in cognition and motor control, but precisely how they contribute to these processes is unclear. Recent studies showing evidence of plasticity in thalamocortical synapses indicate a role for the thalamus in shaping cortical dynamics through learning. Since signals undergo a compression from the cortex to the thalamus, we hypothesized that the computational role of the thalamus depends critically on the structure of corticothalamic connectivity. To test this, we identified the optimal corticothalamic structure that promotes biologically plausible learning in thalamocortical synapses. We found that corticothalamic projections specialized to communicate an efference copy of the cortical output benefit motor control, while communicating the modes of highest variance is optimal for working memory tasks. We analyzed neural recordings from mice performing grasping and delayed discrimination tasks and found corticothalamic communication consistent with these predictions. These results suggest that the thalamus orchestrates cortical dynamics in a functionally precise manner through structured connectivity.

Spindle oscillations in communicating axons within a reconstituted hippocampal formation are strongest in CA3 without thalamus.

Spindle-shaped waves of oscillations emerge in EEG scalp recordings during human and rodent non-REM sleep. The association of these 10-16 Hz oscillations with events during prior wakefulness suggests a role in memory consolidation. Human and rodent depth electrodes in the brain record strong spindles throughout the cortex and hippocampus, with possible origins in the thalamus. However, the source and targets of the spindle oscillations from the hippocampus are unclear. Here, we employed an in vitro reconstruction of four subregions of the hippocampal formation with separate microfluidic tunnels for single axon communication between subregions assembled on top of a microelectrode array. We recorded spontaneous 400-1000 ms long spindle waves at 10-16 Hz in single axons passing between subregions as well as from individual neurons in those subregions. Spindles were nested within slow waves. The highest amplitudes and most frequent occurrence suggest origins in CA3 neurons that send feed-forward axons into CA1 and feedback axons into DG. Spindles had 50-70% slower conduction velocities than spikes and were not phase-locked to spikes suggesting that spindle mechanisms are independent of action potentials. Therefore, consolidation of declarative-cognitive memories in the hippocampus may be separate from the more easily accessible consolidation of memories related to thalamic motor function.

A histological and diceCT-derived 3D reconstruction of the avian visual thalamofugal pathway.

Amniotes feature two principal visual processing systems: the tectofugal and thalamofugal pathways. In most mammals, the thalamofugal pathway predominates, routing retinal afferents through the dorsolateral geniculate complex to the visual cortex. In most birds, the thalamofugal pathway often plays the lesser role with retinal afferents projecting to the principal optic thalami, a complex of several nuclei that resides in the dorsal thalamus. This thalamic complex sends projections to a forebrain structure called the Wulst, the terminus of the thalamofugal visual system. The thalamofugal pathway in birds serves many functions such as pattern discrimination, spatial memory, and navigation/migration. A comprehensive analysis of avian species has unveiled diverse subdivisions within the thalamic and forebrain structures, contingent on species, age, and techniques utilized. In this study, we documented the thalamofugal system in three dimensions by integrating histological and contrast-enhanced computed tomography imaging of the avian brain. Sections of two-week-old chick brains were cut in either coronal, sagittal, or horizontal planes and stained with Nissl and either Gallyas silver or Luxol Fast Blue. The thalamic principal optic complex and pallial Wulst were subdivided on the basis of cell and fiber density. Additionally, we utilized the technique of diffusible iodine-based contrast-enhanced computed tomography (diceCT) on a 5-week-old chick brain, and right eyeball. By merging diceCT data, stained histological sections, and information from the existing literature, a comprehensive three-dimensional model of the avian thalamofugal pathway was constructed. The use of a 3D model provides a clearer understanding of the structural and spatial organization of the thalamofugal system. The ability to integrate histochemical sections with diceCT 3D modeling is critical to better understanding the anatomical and physiologic organization of complex pathways such as the thalamofugal visual system.

A modified neural circuit framework for semantic memory retrieval with implications for circuit modulation to treat verbal retrieval deficits.

Word finding difficulty is a frequent complaint in older age and disease states, but treatment options are lacking for such verbal retrieval deficits. Better understanding of the neurophysiological and neuroanatomical basis of verbal retrieval function may inform effective interventions. In this article, we review the current evidence of a neural retrieval circuit central to verbal production, including words and semantic memory, that involves the pre-supplementary motor area (pre-SMA), striatum (particularly caudate nucleus), and thalamus. We aim to offer a modified neural circuit framework expanded upon a memory retrieval model proposed in 2013 by Hart et al., as evidence from electrophysiological, functional brain imaging, and noninvasive electrical brain stimulation studies have provided additional pieces of information that converge on a shared neural circuit for retrieval of memory and words. We propose that both the left inferior frontal gyrus and fronto-polar regions should be included in the expanded circuit. All these regions have their respective functional roles during verbal retrieval, such as selection and inhibition during search, initiation and termination of search, maintenance of co-activation across cortical regions, as well as final activation of the retrieved information. We will also highlight the structural connectivity from and to the pre-SMA (e.g., frontal aslant tract and fronto-striatal tract) that facilitates communication between the regions within this circuit. Finally, we will discuss how this circuit and its correlated activity may be affected by disease states and how this circuit may serve as a novel target engagement for neuromodulatory treatment of verbal retrieval deficits.

Local contribution to the somatosensory evoked potentials in rat's thalamus.

Local Field Potential (LFP), despite its name, often reflects remote activity. Depending on the orientation and synchrony of their sources, both oscillations and more complex waves may passively spread in brain tissue over long distances and be falsely interpreted as local activity at such distant recording sites. Here we show that the whisker-evoked potentials in the thalamic nuclei are of local origin up to around 6 ms post stimulus, but the later (7-15 ms) wave is overshadowed by a negative component reaching from cortex. This component can be analytically removed and local thalamic LFP can be recovered reliably using Current Source Density analysis. We used model-based kernel CSD (kCSD) method which allowed us to study the contribution of local and distant currents to LFP from rat thalamic nuclei and barrel cortex recorded with multiple, non-linear and non-regular multichannel probes. Importantly, we verified that concurrent recordings from the cortex are not essential for reliable thalamic CSD estimation. The proposed framework can be used to analyze LFP from other brain areas and has consequences for general LFP interpretation and analysis.

Machine learning decoding of single neurons in the thalamus for speech brain-machine interfaces.

Objective. Our goal is to decode firing patterns of single neurons in the left ventralis intermediate nucleus (Vim) of the thalamus, related to speech production, perception, and imagery. For realistic speech brain-machine interfaces (BMIs), we aim to characterize the amount of thalamic neurons necessary for high accuracy decoding.Approach. We intraoperatively recorded single neuron activity in the left Vim of eight neurosurgical patients undergoing implantation of deep brain stimulator or RF lesioning during production, perception and imagery of the five monophthongal vowel sounds. We utilized the Spade decoder, a machine learning algorithm that dynamically learns specific features of firing patterns and is based on sparse decomposition of the high dimensional feature space.Main results. Spade outperformed all algorithms compared with, for all three aspects of speech: production, perception and imagery, and obtained accuracies of 100%, 96%, and 92%, respectively (chance level: 20%) based on pooling together neurons across all patients. The accuracy was logarithmic in the amount of neurons for all three aspects of speech. Regardless of the amount of units employed, production gained highest accuracies, whereas perception and imagery equated with each other.Significance. Our research renders single neuron activity in the left Vim a promising source of inputs to BMIs for restoration of speech faculties for locked-in patients or patients with anarthria or dysarthria to allow them to communicate again. Our characterization of how many neurons are necessary to achieve a certain decoding accuracy is of utmost importance for planning BMI implantation.

Basic Properties of Coordinated Neuronal Ensembles in the Auditory Thalamus.

Coordinated neuronal activity has been identified to play an important role in information processing and transmission in the brain. However, current research predominantly focuses on understanding the properties and functions of neuronal coordination in hippocampal and cortical areas, leaving subcortical regions relatively unexplored. In this study, we use single-unit recordings in female Sprague Dawley rats to investigate the properties and functions of groups of neurons exhibiting coordinated activity in the auditory thalamus-the medial geniculate body (MGB). We reliably identify coordinated neuronal ensembles (cNEs), which are groups of neurons that fire synchronously, in the MGB. cNEs are shown not to be the result of false-positive detections or by-products of slow-state oscillations in anesthetized animals. We demonstrate that cNEs in the MGB have enhanced information-encoding properties over individual neurons. Their neuronal composition is stable between spontaneous and evoked activity, suggesting limited stimulus-induced ensemble dynamics. These MGB cNE properties are similar to what is observed in cNEs in the primary auditory cortex (A1), suggesting that ensembles serve as a ubiquitous mechanism for organizing local networks and play a fundamental role in sensory processing within the brain.

Detection of Threshold-Level Stimuli Modulated by Temporal Predictions of the Cerebellum.

The cerebellum has the reputation of being a primitive part of the brain that mostly is involved in motor coordination and motor control. Older lesion studies and more recent electrophysiological studies have, however, indicated that it is involved in temporal perception and temporal expectation building. An outstanding question is whether this temporal expectation building cerebellar activity has functional relevance. In this study, we collected magnetoencephalographic data from 30 healthy participants performing a detection task on at-threshold stimulation that was presented at the end of a sequence of temporally regular or irregular above-threshold stimulation. We found that behavioral detection rates depended on the degree of irregularity in the sequence preceding it. We also found cerebellar responses evoked by above-threshold and at-threshold stimulation. The evoked responses to at-threshold stimulation differed significantly, depending on whether it was preceded by a regular or an irregular sequence. Finally, we found that detection performance across participants correlated significantly with the differences in cerebellar evoked responses to the at-threshold stimulation, demonstrating the functional relevance of cerebellar activity in sensory expectation building. We furthermore found evidence of thalamic involvement, as indicated by responses in the beta band (14-30 Hz) and by significant modulations of cerebello-thalamic connectivity by the regularity of the sequence and the kind of stimulation terminating the sequence. These results provide evidence that the temporal expectation building mechanism of the cerebellum, what we and others have called an internal clock, shows functional relevance by regulating behavior and performance in sensory action that requires acting and integrating evidence over precise timescales.

Dynamic corticothalamic modulation of the somatosensory thalamocortical circuit during wakefulness.

The feedback projections from cortical layer 6 (L6CT) to the sensory thalamus have long been implicated in playing a primary role in gating sensory signaling but remain poorly understood. To causally elucidate the full range of effects of these projections, we targeted silicon probe recordings to the whisker thalamocortical circuit of awake mice selectively expressing Channelrhodopsin-2 in L6CT neurons. Through optogenetic manipulation of L6CT neurons, multi-site electrophysiological recordings, and modeling of L6CT circuitry, we establish L6CT neurons as dynamic modulators of ongoing spiking in the ventral posteromedial nucleus of the thalamus (VPm), either suppressing or enhancing VPm spiking depending on L6CT neurons' firing rate and synchrony. Differential effects across the cortical excitatory and inhibitory sub-populations point to an overall influence of L6CT feedback on cortical excitability that could have profound implications for regulating sensory signaling across a range of ethologically relevant conditions.

Somatosensory evoked potentials recorded from DBS electrodes: the origin of subcortical N18.

The different peaks of somatosensory-evoked potentials (SEP) originate from a variety of anatomical sites in the central nervous system. The origin of the median nerve subcortical N18 SEP has been studied under various conditions, but the exact site of its generation is still unclear. While it has been claimed to be located in the thalamic region, other studies indicated its possible origin below the pontomedullary junction. Here, we scrutinized and compared SEP recordings from median nerve stimulation through deep brain stimulation (DBS) electrodes implanted in various subcortical targets. We studied 24 patients with dystonia, Parkinson's disease, and chronic pain who underwent quadripolar electrode implantation for chronic DBS and recorded median nerve SEPs from globus pallidus internus (GPi), subthalamic nucleus (STN), thalamic ventral intermediate nucleus (Vim), and ventral posterolateral nucleus (VPL) and the centromedian-parafascicular complex (CM-Pf). The largest amplitude of the triphasic potential of the N18 complex was recorded in Vim. Bipolar recordings confirmed the origin to be close to Vim electrodes (and VPL/CM-Pf) and less close to STN electrodes. GPi recorded only far-field potentials in unipolar derivation. Recordings from DBS electrodes located in different subcortical areas allow determining the origin of certain subcortical SEP waves more precisely. The subcortical N18 of the median nerve SEP-to its largest extent-is generated ventral to the Vim in the region of the prelemniscal radiation/ zona incerta.

Parallel Streams of Direct Corticogeniculate Feedback from Mid-level Extrastriate Cortex in the Macaque Monkey.

First-order thalamic nuclei receive feedforward signals from peripheral receptors and relay these signals to primary sensory cortex. Primary sensory cortex, in turn, provides reciprocal feedback to first-order thalamus. Because the vast majority of sensory thalamocortical inputs target primary sensory cortex, their complementary corticothalamic neurons are assumed to be similarly restricted to primary sensory cortex. We upend this assumption by characterizing morphologically diverse neurons in multiple mid-level visual cortical areas of the primate (Macaca mulatta) brain that provide direct feedback to the primary visual thalamus, the dorsal lateral geniculate nucleus (LGN). Although the majority of geniculocortical neurons project to primary visual cortex (V1), a minority, located mainly in the koniocellular LGN layers, provide direct input to extrastriate visual cortex. These "V1-bypassing" projections may be implicated in blindsight. We hypothesized that geniculocortical inputs directly targeting extrastriate cortex should be complemented by reciprocal corticogeniculate circuits. Using virus-mediated circuit tracing, we discovered corticogeniculate neurons throughout three mid-level extrastriate areas: MT, MST, and V4. Quantitative morphological analyses revealed nonuniform distributions of unique cell types across areas. Many extrastriate corticogeniculate neurons had spiny stellate morphology, suggesting possible targeting of koniocellular LGN layers. Importantly though, multiple morphological types were observed across areas. Such morphological diversity could suggest parallel streams of V1-bypassing corticogeniculate feedback at multiple stages of the visual processing hierarchy. Furthermore, the presence of corticogeniculate neurons across visual cortex necessitates a reevaluation of the LGN as a hub for visual information rather than a simple relay.

Mouse auditory cortex sub-fields receive neuronal projections from MGB subdivisions independently.

Mouse auditory cortex is composed of six sub-fields: primary auditory field (AI), secondary auditory field (AII), anterior auditory field (AAF), insular auditory field (IAF), ultrasonic field (UF) and dorsoposterior field (DP). Previous studies have examined thalamo-cortical connections in the mice auditory system and learned that AI, AAF, and IAF receive inputs from the ventral division of the medial geniculate body (MGB). However, the functional and thalamo-cortical connections between nonprimary auditory cortex (AII, UF, and DP) is unclear. In this study, we examined the locations of neurons projecting to these three cortical sub-fields in the MGB, and addressed the question whether these cortical sub-fields receive inputs from different subsets of MGB neurons or common. To examine the distributions of projecting neurons in the MGB, retrograde tracers were injected into the AII, UF, DP, after identifying these areas by the method of Optical Imaging. Our results indicated that neuron cells which in ventral part of dorsal MGB (MGd) and that of ventral MGB (MGv) projecting to UF and AII with less overlap. And DP only received neuron projecting from MGd. Interestingly, these three cortical areas received input from distinct part of MGd and MGv in an independent manner. Based on our foundings these three auditory cortical sub-fields in mice may independently process auditory information.

Separation of bimodal fMRI responses in mouse somatosensory areas into V1 and non-V1 contributions.

Multisensory integration is necessary for the animal to survive in the real world. While conventional methods have been extensively used to investigate the multisensory integration process in various brain areas, its long-range interactions remain less explored. In this study, our goal was to investigate interactions between visual and somatosensory networks on a whole-brain scale using 15.2-T BOLD fMRI. We compared unimodal to bimodal BOLD fMRI responses and dissected potential cross-modal pathways with silencing of primary visual cortex (V1) by optogenetic stimulation of local GABAergic neurons. Our data showed that the influence of visual stimulus on whisker activity is higher than the influence of whisker stimulus on visual activity. Optogenetic silencing of V1 revealed that visual information is conveyed to whisker processing via both V1 and non-V1 pathways. The first-order ventral posteromedial thalamic nucleus (VPM) was functionally affected by non-V1 sources, while the higher-order posterior medial thalamic nucleus (POm) was predominantly modulated by V1 but not non-V1 inputs. The primary somatosensory barrel field (S1BF) was influenced by both V1 and non-V1 inputs. These observations provide valuable insights for into the integration of whisker and visual sensory information.

Amplitude Adaptive Modulation of Neural Oscillations Over Long-Term Dynamic Conditions: A Computational Study.

Closed-loop deep brain stimulation (DBS) shows great potential for precise neuromodulation of various neurological disorders, particularly Parkinson's disease (PD). However, substantial challenges remain in clinical translation due to the complex programming procedure of closed-loop DBS parameters. In this study, we proposed an online optimized amplitude adaptive strategy based on the particle swarm optimization (PSO) and proportional-integral-differential (PID) controller for modulation of the beta oscillation in a PD mean field model over long-term dynamic conditions. The strategy aimed to calculate the stimulation amplitude adapting to the fluctuations caused by circadian rhythm, medication rhythm, and stochasticity in the basal ganglia-thalamus-cortical circuit. The PID gains were optimized online using PSO, based on modulation accuracy, mean stimulation amplitude, and stimulation variation. The results showed that the proposed strategy optimized the stimulation amplitude and achieved beta power modulation under the influence of circadian rhythm, medication rhythm, and stochasticity of beta oscillations. This work offers a novel approach for precise neuromodulation with the potential for clinical translation.

Single neurons in the thalamus and subthalamic nucleus process cardiac and respiratory signals in humans.

Visceral signals are constantly processed by our central nervous system, enable homeostatic regulation, and influence perception, emotion, and cognition. While visceral processes at the cortical level have been extensively studied using non-invasive imaging techniques, very few studies have investigated how this information is processed at the single neuron level, both in humans and animals. Subcortical regions, relaying signals from peripheral interoceptors to cortical structures, are particularly understudied and how visceral information is processed in thalamic and subthalamic structures remains largely unknown. Here, we took advantage of intraoperative microelectrode recordings in patients undergoing surgery for deep brain stimulation (DBS) to investigate the activity of single neurons related to cardiac and respiratory functions in three subcortical regions: ventral intermedius nucleus (Vim) and ventral caudalis nucleus (Vc) of the thalamus, and subthalamic nucleus (STN). We report that the activity of a large portion of the recorded neurons (about 70%) was modulated by either the heartbeat, the cardiac inter-beat interval, or the respiration. These cardiac and respiratory response patterns varied largely across neurons both in terms of timing and their kind of modulation. A substantial proportion of these visceral neurons (30%) was responsive to more than one of the tested signals, underlining specialization and integration of cardiac and respiratory signals in STN and thalamic neurons. By extensively describing single unit activity related to cardiorespiratory function in thalamic and subthalamic neurons, our results highlight the major role of these subcortical regions in the processing of visceral signals.

Ocular surface information seen from the somatosensory thalamus and cortex.

Ocular Surface (OS) somatosensory innervation detects external stimuli producing perceptions, such as pain or dryness, the most relevant symptoms in many OS pathologies. Nevertheless, little is known about the central nervous system circuits involved in these perceptions, and how they integrate multimodal inputs in general. Here, we aim to describe the thalamic and cortical activity in response to OS stimulation of different modalities. Electrophysiological extracellular recordings in anaesthetized rats were used to record neural activity, while saline drops at different temperatures were applied to stimulate the OS. Neurons were recorded in the ophthalmic branch of the trigeminal ganglion (TG, 49 units), the thalamic VPM-POm nuclei representing the face (Th, 69 units) and the primary somatosensory cortex (S1, 101 units). The precise locations for Th and S1 neurons receiving OS information are reported here for the first time. Interestingly, all recorded nuclei encode modality both at the single neuron and population levels, with noxious stimulation producing a qualitatively different activity profile from other modalities. Moreover, neurons responding to new combinations of stimulus modalities not present in the peripheral TG subsequently appear in Th and S1, being organized in space through the formation of clusters. Besides, neurons that present higher multimodality display higher spontaneous activity. These results constitute the first anatomical and functional characterization of the thalamocortical representation of the OS. Furthermore, they provide insight into how information from different modalities gets integrated from the peripheral nervous system into the complex cortical networks of the brain. KEY POINTS: Anatomical location of thalamic and cortical ocular surface representation. Thalamic and cortical neuronal responses to multimodal stimulation of the ocular surface. Increasing functional complexity along trigeminal neuroaxis. Proposal of a new perspective on how peripheral activity shapes central nervous system function.

Rebuilding the behavioral inhibition circuit to prevent opioid relapse.

Failure in behavioral suppression is a key feature in substance use disorders, potentially leading to compulsive drug seeking and relapse. In this issue of Neuron, Paniccia et al.1 elucidated a heroin-damaged paraventricular nucleus of the thalamus (PVT)-accumbal circuit and how recovery of PVT function could prevent heroin relapse.